Ring loss: Convex Feature Normalization for Face Recognition

CVPR 2018 Yutong ZhengDipan K. PalMarios Savvides

We motivate and present Ring loss, a simple and elegant feature normalization approach for deep networks designed to augment standard loss functions such as Softmax. We argue that deep feature normalization is an important aspect of supervised classification problems where we require the model to represent each class in a multi-class problem equally well... (read more)

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Evaluation results from the paper


Task Dataset Model Metric name Metric value Global rank Compare
Face Verification Labeled Faces in the Wild Ring loss Accuracy 99.52% # 4